Dockerfile

@@ -1,23 +1,20 @@
 FROM python:3.10-slim
 
-ENV FLASK_APP=src/app.py
-ARG PIP_REQ_FILE=requirements.txt
-
 WORKDIR /app
 
-RUN apt update && apt install git ffmpeg -y && \
+COPY requirements.txt /app
-    pip3 install "git+https://github.com/openai/whisper.git"
+RUN apt-get update && apt-get install git -y
+RUN pip3 install -r requirements.txt
+RUN pip3 install "git+https://github.com/openai/whisper.git" 
+RUN apt-get install -y ffmpeg
 
-RUN whisper --model medium --language ru dummy.wav; exit 0 && \
+RUN whisper --model medium --language ru dummy.wav; exit 0
-    whisper --model small --language ru dummy.wav; exit 0
+RUN whisper --model small --language ru dummy.wav; exit 0
 
-COPY src/ src/
+COPY . .
-
-# Separate requirements installation to keep other dependencies
-# in cache
-COPY ${PIP_REQ_FILE} ${PIP_REQ_FILE}
-RUN pip3 install -r ${PIP_REQ_FILE}
 
 EXPOSE 5000
 
+ENV FLASK_APP=src/app.py
+
 CMD [ "python3", "-m" , "flask", "run", "--host=0.0.0.0"]

Makefile

@@ -1,7 +0,0 @@
-run:
-	PYTORCH_NO_CUDA_MEMORY_CACHING=1 \
-	PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \
-	CUDA_LAUNCH_BLOCKING=1 \
-	FLASK_APP=src/app.py \
-	PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:128 \
-	flask run --host=0.0.0.0

requirements.txt

@@ -1,62 +1,8 @@
-asgiref==3.7.2
+flask==3.0.2
-av==11.0.0
-blinker==1.7.0
-certifi==2024.2.2
-charset-normalizer==3.3.2
-click==8.1.7
-coloredlogs==15.0.1
-ctranslate2==4.0.0
-Cython==3.0.8
-dtw-python==1.3.1
-faster-whisper==1.0.0
-filelock==3.13.1
-Flask==3.0.2
-flatbuffers==23.5.26
-fsspec==2024.2.0
-huggingface-hub==0.21.3
-humanfriendly==10.0
-idna==3.6
-itsdangerous==2.1.2
 Jinja2==3.1.3
-llvmlite==0.42.0
+blinker==1.7.0
-MarkupSafe==2.1.5
-more-itertools==10.2.0
-mpmath==1.3.0
-networkx==3.2.1
-numba==0.59.0
-numpy==1.26.4
-nvidia-cublas-cu12==12.1.3.1
-nvidia-cuda-cupti-cu12==12.1.105
-nvidia-cuda-nvrtc-cu12==12.1.105
-nvidia-cuda-runtime-cu12==12.1.105
-nvidia-cudnn-cu12==8.9.2.26
-nvidia-cufft-cu12==11.0.2.54
-nvidia-curand-cu12==10.3.2.106
-nvidia-cusolver-cu12==11.4.5.107
-nvidia-cusparse-cu12==12.1.0.106
-nvidia-nccl-cu12==2.19.3
-nvidia-nvjitlink-cu12==12.3.101
-nvidia-nvtx-cu12==12.1.105
-onnxruntime==1.17.1
-openai-whisper @ git+https://github.com/openai/whisper.git@ba3f3cd54b0e5b8ce1ab3de13e32122d0d5f98ab
-packaging==23.2
-pillow==10.2.0
-protobuf==4.25.3
-python-dotenv==1.0.1
-PyYAML==6.0.1
-regex==2023.12.25
-requests==2.31.0
-scipy==1.12.0
-six==1.16.0
-sympy==1.12
-tiktoken==0.6.0
-tokenizers==0.15.2
-torch==2.2.1
-torchaudio==2.2.1
-torchvision==0.17.1
-tqdm==4.66.2
-triton==2.2.0
-typing_extensions==4.10.0
-urllib3==2.2.1
 Werkzeug==3.0.1
-whisper-timestamped==1.15.0
+click==8.1.7
+itsdangerous==2.1.2
+MarkupSafe==2.1.5
+python-dotenv==1.0.1

src/app.py

@@ -1,59 +1,67 @@
 from flask import Flask, abort, request
 from tempfile import NamedTemporaryFile
-
+from dotenv import load_dotenv
+import os
+import whisper
+import torch
 import sys
+import re
 
-import config
+load_dotenv()
 
-from queue_stack import QueueStack
+HARPYIA_PROMPT = os.getenv('HARPYIA_PROMPT') or 'спасите помогите на помощь пожар'
-from queue_stack.strategies import RecognizeAndSendStrategy
+HARPYIA_MODEL = os.getenv('HARPYIA_MODEL') or 'medium'
+HARPYIA_LANGUAGE = os.getenv('HARPYIA_LANGUAGE') or 'ru'
 
-from recognizer import Recognizer
+# Check if NVIDIA GPU is available
-from recognizer.strategies import WhisperStrategy, FastWhisperStrategy
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 
-from message import MessageService
+# Load the Whisper model:
-from message.strategies import SosMessageStrategy, NumberMessageStrategy
+model = whisper.load_model(HARPYIA_MODEL, device=DEVICE)
 
 app = Flask(__name__)
 
-whisper_recognizer = Recognizer(WhisperStrategy())
-fast_whisper_recognizer = Recognizer(FastWhisperStrategy())
-
-sos_message_service = MessageService(SosMessageStrategy())
-number_message_service = MessageService(NumberMessageStrategy())
-
-queue_stack = QueueStack(RecognizeAndSendStrategy())
-queue_stack.start_loop_in_thread()
-
 @app.route("/")
 def hello():
-  return "To recognize an audio file, upload it using a POST request with '/recognize' or '/recognize-number' route."
+    return "To recognize an audio file, upload it using a POST request with '/recognize' or '/recognize_number' route."
 
-def recognize_files(message_service: MessageService):
+def recognize_files(handler_fn):
-  if not request.files:
+    if not request.files:
-    abort(400)
+        abort(400)
 
-  results = []
+    results = []
 
-  for filename, handle in request.files.items():
+    for filename, handle in request.files.items():
-    temp = NamedTemporaryFile()
+        temp = NamedTemporaryFile()
-    handle.save(temp)
+        handle.save(temp)
+        result = model.transcribe(temp.name, language=HARPYIA_LANGUAGE, initial_prompt=HARPYIA_PROMPT)
+        results.append({
+            'filename': filename,
+            'transcript': handler_fn(result['text']),
+        })
 
-    results.append(queue_stack.append_and_await((
+    print(results, file=sys.stderr)
-      temp, 
+    return {'results': results}
-      whisper_recognizer, 
-      message_service,
-      config.HARPYIA_LANGUAGE,
-      message_service.get_prompt()
-    )))
-
-  print(results, file=sys.stderr)
-  return {'results': results}
 
 @app.route('/recognize', methods=['POST'])
 def recognize():
-  return recognize_files(sos_message_service)
+    return recognize_files(lambda text: text)
 
-@app.route('/recognize-number', methods=['POST'])
+@app.route('/recognize_number', methods=['POST'])
 def recognize_number():
-  return recognize_files(number_message_service)
+    return recognize_files(transfer_and_clean)
+
+def transfer_and_clean(input_string):
+    number_mapping = {
+        "один": "1",
+        "два": "2",
+        "три": "3"
+    }
+
+    for word, number in number_mapping.items():
+        input_string = input_string.replace(word, number)
+    
+    input_string = re.sub(r'[^\d]+', '', input_string)
+    
+    return input_string
+

src/config.py

@@ -1,21 +0,0 @@
-import os
-import torch
-from dotenv import load_dotenv
-
-load_dotenv()
-
-HARPYIA_MODEL = os.getenv('HARPYIA_MODEL') or 'small'
-HARPYIA_LANGUAGE = os.getenv('HARPYIA_LANGUAGE') or 'ru'
-HARPYIA_SAMPLE_RATE = os.getenv('HARPYIA_SAMPLE_RATE') or 160000
-
-WHISPER_NUM_WORKERS = os.getenv('WHISPER_NUM_WORKERS') or 6
-WHISPER_CPU_THREADS = os.getenv('WHISPER_CPU_THREADS') or 10
-WHISPER_BEAM_SIZE = os.getenv('WHISPER_BEAM_SIZE') or 5
-
-SOS_PROMPT = os.getenv('SOS_PROMPT') or 'спасите помогите помощь пожар караул кирилл'
-NUMBER_PROMPT = os.getenv('NUMBER_PROMPT') or 'один два три четыре пять шесть семь восемь девять десять одинадцать двенадцать тринадцать сто сот'
-
-RAT_URL = os.getenv('RAT_URL') or 'localhost:8081'
-
-# Check if NVIDIA GPU is available
-DEVICE = "cuda" if torch.cuda.is_available() else "cpu"

src/message/__init__.py

@@ -1 +0,0 @@
-from message.message_service import MessageService

src/message/message_service.py

@@ -1,24 +0,0 @@
-import sys
-from message.strategies import BaseMessageStrategy
-
-class MessageService:
-  def __init__(self, strategy: BaseMessageStrategy) -> None:
-    self._strategy = strategy
-
-  def get_prompt(self) -> str:
-    self._strategy.get_prompt()
-
-  def transfer(self, text: str) -> any:
-    return self._strategy.transfer(text)
-
-  def send(self, message: str) -> any:
-    self._strategy.send(message)
-
-  def transfer_and_send(self, recognized_result: any) -> any:
-    message = self.transfer(recognized_result)
-
-    if message:
-      self.send(message)
-
-    print('Sending message:', recognized_result, file=sys.stderr)
-    return message

src/message/strategies/__init__.py

@@ -1,3 +0,0 @@
-from message.strategies.base_message_strategy import BaseMessageStrategy
-from message.strategies.sos_message_strategy import SosMessageStrategy
-from message.strategies.number_message_strategy import NumberMessageStrategy

src/message/strategies/base_message_strategy.py

@@ -1,14 +0,0 @@
-from abc import ABC, abstractmethod
-
-class BaseMessageStrategy(ABC):
-  @abstractmethod
-  def get_prompt() -> str:
-    pass
-
-  @abstractmethod
-  def transfer(self, text: str) -> any:
-    pass
-
-  @abstractmethod
-  def send(self, message: str) -> any:
-    pass

src/message/strategies/number_message_strategy.py

@@ -1,31 +0,0 @@
-import re
-
-import config
-from message.strategies import BaseMessageStrategy
-
-class NumberMessageStrategy(BaseMessageStrategy):
-  def __init__(self, prompt=config.NUMBER_PROMPT) -> None:
-    self._prompt = prompt
-
-  def get_prompt(self):
-    return self._prompt
-
-  def transfer(self, recognized_result: any) -> str:
-    return self._transfer_and_clean(recognized_result['text'])
-
-  def _transfer_and_clean(self, text: str) -> str:
-    number_mapping = {
-      "один": "1",
-      "два": "2",
-      "три": "3"
-    }
-
-    for word, number in number_mapping.items():
-      transfered_text = text.replace(word, number)
-    
-    transfered_text = re.sub(r'[^\d]+', '', transfered_text)
-    
-    return {'recognized': transfered_text}
-
-  def send(self, message: str) -> None:
-    pass

src/message/strategies/sos_message_strategy.py

@@ -1,35 +0,0 @@
-from typing import List
-import requests
-
-import config
-from message.strategies import BaseMessageStrategy
-
-MESSAGE_ENDPOINT = '/message'
-
-class SosMessageStrategy(BaseMessageStrategy):
-  def __init__(self, prompt=config.SOS_PROMPT, url=config.RAT_URL) -> None:
-    self._prompt = prompt
-    self._url = url
-
-  def get_prompt(self):
-    return self._prompt
-
-  def transfer(self, recognized_result: any) -> str:
-    return {
-      'transcript': recognized_result['text'],
-      'results': self._filter_words_with_prompt(recognized_result['text']),
-      'segments': recognized_result['segments']
-    }
-
-  def _filter_words_with_prompt(self, text: str) -> str:
-    words = []
-
-    for prompt in self._prompt.split(' '):
-      if prompt in text.lower():
-        words.append(prompt)
-
-    return words
-
-  def send(self, message) -> any:
-    pass
-    #return requests.post(self._url + MESSAGE_ENDPOINT, json={'message': message})

src/queue_stack/__init__.py

@@ -1 +0,0 @@
-from queue_stack.queue_stack import QueueStack

src/queue_stack/queue_stack.py

@@ -1,51 +0,0 @@
-import sys
-
-from threading import Thread, Event, Lock
-
-from queue_stack.strategies import BaseProcessStrategy
-
-class QueueStack:
-  def __init__(self, strategy: BaseProcessStrategy) -> None:
-    self._stack = []
-    self._strategy = strategy
-  
-    self._lock = Lock()
-    self._running = False
-
-    self._last_response = None
-
-  def append(self, args, event=None) -> None:
-    with self._lock:
-      self._stack.append((args, event))
-
-  def append_and_await(self, args) -> any:
-    event = Event()
-    self.append(args, event=event)
-
-    event.wait()
-    event.clear()
-
-    return self._last_response
-
-  def loop(self) -> None:
-    self._running = True
-
-    while self._running:
-      with self._lock:
-        if self._stack:
-          print('Stack length:', len(self._stack), file=sys.stderr)
-          (args, event) = self._stack.pop(0)
-          self._last_response = self._process(*args)
-
-          if event:
-            event.set()
-
-  def _process(self, *args, **kwargs) -> any:
-    return self._strategy.process(*args, **kwargs)
-
-  def start_loop_in_thread(self) -> None:
-    thread = Thread(target=self.loop)
-    thread.start()
-
-  def stop_loop(self) -> None:
-    self._running = False

src/queue_stack/strategies/__init__.py

@@ -1,2 +0,0 @@
-from queue_stack.strategies.base_process_strategy import BaseProcessStrategy
-from queue_stack.strategies.recognize_and_send_strategy import RecognizeAndSendStrategy

src/queue_stack/strategies/base_process_strategy.py

@@ -1,6 +0,0 @@
-from abc import ABC, abstractmethod
-
-class BaseProcessStrategy(ABC):
-  @abstractmethod
-  def process(self, *args, **kwargs) -> any:
-    pass

src/queue_stack/strategies/recognize_and_send_strategy.py

@@ -1,14 +0,0 @@
-import sys
-
-from queue_stack.strategies import BaseProcessStrategy
-from message import MessageService
-from recognizer import Recognizer
-
-class RecognizeAndSendStrategy(BaseProcessStrategy):
-  def process(self, file, recognizer: Recognizer, message_service: MessageService, language, prompt) -> any:
-
-    result = recognizer.recognize(file, language=language, prompt=prompt)
-    message = message_service.transfer_and_send(result)
-    print(message, file=sys.stderr)
-
-    return message

src/recognizer/__init__.py

@@ -1 +0,0 @@
-from recognizer.recognizer import Recognizer

src/recognizer/recognizer.py

@@ -1,14 +0,0 @@
-import sys
-
-import config
-from recognizer.strategies import BaseRecognizerStrategy
-
-class Recognizer:
-  def __init__(self, strategy: BaseRecognizerStrategy) -> None:
-    self._strategy = strategy
-
-  def recognize(self, file, language, prompt) -> str:
-    result = self._strategy.recognize(file, language=language, prompt=prompt)
-
-    print(f'Result: {result}', file=sys.stderr)
-    return result

src/recognizer/strategies/__init__.py

@@ -1,3 +0,0 @@
-from recognizer.strategies.base_recognizer_strategy import BaseRecognizerStrategy
-from recognizer.strategies.whisper_strategy import WhisperStrategy
-from recognizer.strategies.fast_whisper_strategy import FastWhisperStrategy

src/recognizer/strategies/base_recognizer_strategy.py

@@ -1,6 +0,0 @@
-from abc import ABC, abstractmethod
-
-class BaseRecognizerStrategy(ABC):
-  @abstractmethod
-  def recognize(self, file, language, prompt) -> any:
-    pass

src/recognizer/strategies/fast_whisper_strategy.py

@@ -1,59 +0,0 @@
-import sys
-
-import whisper
-from faster_whisper import WhisperModel
-
-import config
-from recognizer.strategies import BaseRecognizerStrategy
-
-class FastWhisperStrategy(BaseRecognizerStrategy):
-  def __init__(self) -> None:
-    self._model = WhisperModel(
-      model_size_or_path=config.HARPYIA_MODEL,
-      device=config.DEVICE,
-      num_workers=config.WHISPER_NUM_WORKERS,
-      cpu_threads=config.WHISPER_CPU_THREADS
-    )
-
-  def recognize(self, file, language, prompt) -> any:
-    audio = self._prepare_file(file.name)
-    return self._transcribe(audio, language, prompt)
-
-  def _prepare_file(self, filename: str):
-    audio = whisper.load_audio(filename, sr=config.HARPYIA_SAMPLE_RATE)
-    audio = whisper.pad_or_trim(audio)
-    return audio
-
-  def _transcribe(self, audio, language, prompt):
-    segments, _ = self._model.transcribe(
-      audio,
-      language=language,
-      initial_prompt=prompt,
-      condition_on_previous_text=False,
-      vad_filter=True,
-      beam_size=config.WHISPER_BEAM_SIZE,
-    )
-
-    print('Segments:', file=sys.stderr)
-    for i in segments:
-      print(i, file=sys.stderr)
-
-    words = []
-    for segment in list(segments):
-      words.append(segment.text)
-
-    return {
-      'text': ' '.join(words),
-      'segments': {
-        'id': None,
-        'seek': None,
-        'start': None,
-        'end': None,
-        'text': None,
-        'tokens': None,
-        'temperature': None,
-        'avg_logprob': None,
-        'compression_ratio': None,
-        'no_speech_prob': None,
-      }
-    }

src/recognizer/strategies/whisper_strategy.py

@@ -1,12 +0,0 @@
-import whisper
-
-import config
-from recognizer.strategies import BaseRecognizerStrategy
-
-class WhisperStrategy(BaseRecognizerStrategy):
-  def __init__(self) -> None:
-    self._model = whisper.load_model(config.HARPYIA_MODEL, device=config.DEVICE)
-
-  def recognize(self, file, language, prompt) -> any:
-    return self._model.transcribe(file.name, \
-      language=language, initial_prompt=prompt)